Business Cases for Data Science

Business Case 1 - Predict Hotel Booking Cancellations

Group AA

Members:

Table of Contents

  1. Business Understanding

  2. Data Understanding

  3. Data Preparation

  4. Modeling

  5. Evaluation

  6. Deployment

1. Business Understanding

Company wants to understand the behavior of their customers based on the cancellations. They want to identify which customers are more likely to cancel their bookings and achieve these goals:

Project Plan

Phase Time Resources Risks
Business Understanding 1 day All analysts Economic and market changes
Data Understanding 1 day All analysts Data problems, technological problems
Data Preparation 2 days Data scientists, DB engineers Data problems, technological problems
Modeling 1 day Data scientists Technological problems, inability to build adequate model
Evaluation 1 day All analysts Economic change inability to implement results
Deployment 1 day Data scientists, DB engineers, implementation team Economic change inability to implement results

2. Data Understanding

Dataset description

3. Data Preparation

3.1. Handling missing values

3.2. Outliers

3.3 Feature engineering

3.4. Feature Selection

3.5. Encoding

3.6. Scaling

4. Modeling

4.1 Random Forest

4.2 Gradient Boosting

4.3 XGBoost

5. Evaluation

5.1 Stacking

From the result, it is clear that the model of XGBoost showed the best performance